英文标题：
《Stochastic model of financial markets reproducing scaling and memory in
  volatility return intervals》
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作者：
Vygintas Gontis, Shlomo Havlin, Aleksejus Kononovicius, Boris
  Podobnik, H. Eugene Stanley
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最新提交年份：
2016
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英文摘要：
  We investigate the volatility return intervals in the NYSE and FOREX markets. We explain previous empirical findings using a model based on the interacting agent hypothesis instead of the widely-used efficient market hypothesis. We derive macroscopic equations based on the microscopic herding interactions of agents and find that they are able to reproduce various stylized facts of different markets and different assets with the same set of model parameters. We show that the power-law properties and the scaling of return intervals and other financial variables have a similar origin and could be a result of a general class of non-linear stochastic differential equations derived from a master equation of an agent system that is coupled by herding interactions. Specifically, we find that this approach enables us to recover the volatility return interval statistics as well as volatility probability and spectral densities for the NYSE and FOREX markets, for different assets, and for different time-scales. We find also that the historical S\\&P500 monthly series exhibits the same volatility return interval properties recovered by our proposed model. Our statistical results suggest that human herding is so strong that it persists even when other evolving fluctuations perturbate the financial system.
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中文摘要：
我们研究了纽约证券交易所和外汇市场的波动收益区间。我们用一个基于交互作用主体假说而非广泛使用的有效市场假说的模型来解释以前的实证结果。我们基于微观的羊群相互作用推导出宏观方程，发现它们能够用同一组模型参数再现不同市场和不同资产的各种风格化事实。我们证明了幂律性质以及收益区间和其他金融变量的标度具有相似的起源，并且可能是由一个由羊群相互作用耦合的主体系统的主方程导出的一类一般非线性随机微分方程的结果。具体而言，我们发现，这种方法使我们能够恢复纽约证券交易所和外汇市场、不同资产和不同时间尺度的波动收益区间统计数据以及波动概率和频谱密度。我们还发现，历史S\\&P500月度序列表现出与我们提出的模型恢复的波动-收益区间性质相同的波动性。我们的统计结果表明，人类的羊群行为非常强烈，即使其他不断变化的波动扰乱了金融系统，这种行为也会持续。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：General Finance        一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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